{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: sqlalchemy in d:\\anaconda\\lib\\site-packages (2.0.30)\n",
      "Requirement already satisfied: typing-extensions>=4.6.0 in d:\\anaconda\\lib\\site-packages (from sqlalchemy) (4.11.0)\n",
      "Requirement already satisfied: greenlet!=0.4.17 in d:\\anaconda\\lib\\site-packages (from sqlalchemy) (3.0.1)\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: pymysql in d:\\anaconda\\lib\\site-packages (1.1.1)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install sqlalchemy\n",
    "%pip install pymysql"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: mysql-connector-python in d:\\anaconda\\lib\\site-packages (9.2.0)Note: you may need to restart the kernel to use updated packages.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%pip install mysql-connector-python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pymysql\n",
    "pymysql.install_as_MySQLdb()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: scikit-learn in d:\\anaconda\\lib\\site-packages (1.4.2)\n",
      "Requirement already satisfied: numpy>=1.19.5 in d:\\anaconda\\lib\\site-packages (from scikit-learn) (1.26.4)\n",
      "Requirement already satisfied: scipy>=1.6.0 in d:\\anaconda\\lib\\site-packages (from scikit-learn) (1.13.1)\n",
      "Requirement already satisfied: joblib>=1.2.0 in d:\\anaconda\\lib\\site-packages (from scikit-learn) (1.4.2)\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in d:\\anaconda\\lib\\site-packages (from scikit-learn) (2.2.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install scikit-learn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import mysql.connector\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import tushare as ts\n",
    "import MySQLdb as mdb\n",
    "\n",
    "import matplotlib\n",
    "matplotlib.use (\"TkAgg\")\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "from matplotlib.collections import LineCollection\n",
    "\n",
    "import pandas as pd\n",
    "from sklearn import cluster,covariance,manifold\n",
    "\n",
    "from matplotlib.font_manager import FontProperties\n",
    "\n",
    "import tushare as ts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "pro = ts.pro_api('f78a738f8ce5bae4e6ebc54275bd2f404fc57e63500faa27db486cf1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:2: SyntaxWarning: invalid escape sequence '\\p'\n",
      "<>:2: SyntaxWarning: invalid escape sequence '\\p'\n",
      "C:\\Users\\LWJ\\AppData\\Local\\Temp\\ipykernel_22748\\3842405405.py:2: SyntaxWarning: invalid escape sequence '\\p'\n",
      "  sys.path.append(\"D:\\python\\Lib\\site-packages\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        ts_code trade_date   open   high    low  close  pre_close  change  \\\n",
      "0     920128.BJ   20250124  28.35  28.35  27.70  27.80      27.94   -0.14   \n",
      "1     920118.BJ   20250124  24.10  24.59  24.01  24.42      24.29    0.13   \n",
      "2     920116.BJ   20250124  48.00  48.75  47.03  47.80      48.25   -0.45   \n",
      "3     920111.BJ   20250124  24.09  24.87  24.09  24.47      24.55   -0.08   \n",
      "4     920106.BJ   20250124  56.49  58.37  56.25  57.18      55.20    1.98   \n",
      "...         ...        ...    ...    ...    ...    ...        ...     ...   \n",
      "5995  688244.SH   20250123  27.50  27.50  25.03  25.03      27.60   -2.57   \n",
      "5996  688239.SH   20250123  42.18  42.89  41.70  42.05      42.35   -0.30   \n",
      "5997  688238.SH   20250123   4.62   4.69   4.56   4.57       4.58   -0.01   \n",
      "5998  688237.SH   20250123  22.07  22.70  22.01  22.12      22.04    0.08   \n",
      "5999  688236.SH   20250123  11.75  11.88  11.65  11.67      11.65    0.02   \n",
      "\n",
      "      pct_chg       vol      amount  \n",
      "0     -0.5011   6781.63   18964.081  \n",
      "1      0.5352   1835.70    4476.014  \n",
      "2     -0.9326  44587.15  212700.177  \n",
      "3     -0.3259  18705.00   45877.959  \n",
      "4      3.5870  11257.92   64668.158  \n",
      "...       ...       ...         ...  \n",
      "5995  -9.3116  38866.22  101725.871  \n",
      "5996  -0.7084  45896.07  194526.692  \n",
      "5997  -0.2183  67083.12   31159.039  \n",
      "5998   0.3630   7334.50   16382.255  \n",
      "5999   0.1717  11154.25   13117.054  \n",
      "\n",
      "[6000 rows x 11 columns]\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "sys.path.append(\"D:\\python\\Lib\\site-packages\")\n",
    "import tushare as ts\n",
    "ts.set_token('f78a738f8ce5bae4e6ebc54275bd2f404fc57e63500faa27db486cf1')\n",
    "pro = ts.pro_api()\n",
    "\n",
    "params = {\n",
    "    \"ts_code\": \"601939.SH\",\n",
    "    \"trade_date\": \"\",\n",
    "    \"start_date\": 20100101,\n",
    "    \"end_date\": 20241225,\n",
    "    \"offset\": \"\",\n",
    "    \"limit\": \"\",\n",
    "    \"fields\": [\n",
    "        \"ts_code\",\n",
    "        \"trade_date\",\n",
    "        \"open\",\n",
    "        \"high\",\n",
    "        \"low\",\n",
    "        \"close\",\n",
    "        \"pre_close\",\n",
    "        \"change\",\n",
    "        \"pct_close\",\n",
    "        \"change\",\n",
    "        \"pct_chg\",\n",
    "        \"vol\",\n",
    "        \"amount\"\n",
    "    ]\n",
    "}\n",
    "df = pro.daily(params)\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting mplfinanceNote: you may need to restart the kernel to use updated packages.\n",
      "\n",
      "  Downloading mplfinance-0.12.10b0-py3-none-any.whl.metadata (19 kB)\n",
      "Requirement already satisfied: matplotlib in d:\\anaconda\\lib\\site-packages (from mplfinance) (3.8.4)\n",
      "Requirement already satisfied: pandas in d:\\anaconda\\lib\\site-packages (from mplfinance) (2.2.2)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in d:\\anaconda\\lib\\site-packages (from matplotlib->mplfinance) (1.2.0)\n",
      "Requirement already satisfied: cycler>=0.10 in d:\\anaconda\\lib\\site-packages (from matplotlib->mplfinance) (0.11.0)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in d:\\anaconda\\lib\\site-packages (from matplotlib->mplfinance) (4.51.0)\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in d:\\anaconda\\lib\\site-packages (from matplotlib->mplfinance) (1.4.4)\n",
      "Requirement already satisfied: numpy>=1.21 in d:\\anaconda\\lib\\site-packages (from matplotlib->mplfinance) (1.26.4)\n",
      "Requirement already satisfied: packaging>=20.0 in d:\\anaconda\\lib\\site-packages (from matplotlib->mplfinance) (23.2)\n",
      "Requirement already satisfied: pillow>=8 in d:\\anaconda\\lib\\site-packages (from matplotlib->mplfinance) (10.3.0)\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in d:\\anaconda\\lib\\site-packages (from matplotlib->mplfinance) (3.0.9)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in d:\\anaconda\\lib\\site-packages (from matplotlib->mplfinance) (2.9.0.post0)\n",
      "Requirement already satisfied: pytz>=2020.1 in d:\\anaconda\\lib\\site-packages (from pandas->mplfinance) (2024.1)\n",
      "Requirement already satisfied: tzdata>=2022.7 in d:\\anaconda\\lib\\site-packages (from pandas->mplfinance) (2023.3)\n",
      "Requirement already satisfied: six>=1.5 in d:\\anaconda\\lib\\site-packages (from python-dateutil>=2.7->matplotlib->mplfinance) (1.16.0)\n",
      "Downloading mplfinance-0.12.10b0-py3-none-any.whl (75 kB)\n",
      "   ---------------------------------------- 0.0/75.0 kB ? eta -:--:--\n",
      "   ---------------- ----------------------- 30.7/75.0 kB 1.3 MB/s eta 0:00:01\n",
      "   ---------------- ----------------------- 30.7/75.0 kB 1.3 MB/s eta 0:00:01\n",
      "   ---------------- ----------------------- 30.7/75.0 kB 1.3 MB/s eta 0:00:01\n",
      "   ---------------- ----------------------- 30.7/75.0 kB 1.3 MB/s eta 0:00:01\n",
      "   ---------------- ----------------------- 30.7/75.0 kB 1.3 MB/s eta 0:00:01\n",
      "   --------------------- ------------------ 41.0/75.0 kB 151.3 kB/s eta 0:00:01\n",
      "   -------------------------------- ------- 61.4/75.0 kB 204.8 kB/s eta 0:00:01\n",
      "   -------------------------------------- - 71.7/75.0 kB 196.9 kB/s eta 0:00:01\n",
      "   ---------------------------------------- 75.0/75.0 kB 188.3 kB/s eta 0:00:00\n",
      "Installing collected packages: mplfinance\n",
      "Successfully installed mplfinance-0.12.10b0\n"
     ]
    }
   ],
   "source": [
    "%pip install mplfinance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\LWJ\\AppData\\Local\\Temp\\ipykernel_22748\\888090635.py:31: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  if data['Close'][i] >= data['Open'][i]:\n",
      "C:\\Users\\LWJ\\AppData\\Local\\Temp\\ipykernel_22748\\888090635.py:37: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  lower = data['Close'][i]\n",
      "C:\\Users\\LWJ\\AppData\\Local\\Temp\\ipykernel_22748\\888090635.py:38: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  height = data['Open'][i] - data['Close'][i]\n",
      "C:\\Users\\LWJ\\AppData\\Local\\Temp\\ipykernel_22748\\888090635.py:45: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  ax.plot([i-0.6, i+0.6], [data['High'][i], data['High'][i]], color='k')\n",
      "C:\\Users\\LWJ\\AppData\\Local\\Temp\\ipykernel_22748\\888090635.py:46: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  ax.plot([i-0.6, i+0.6], [data['Low'][i], data['Low'][i]], color='k')\n",
      "C:\\Users\\LWJ\\AppData\\Local\\Temp\\ipykernel_22748\\888090635.py:33: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  lower = data['Open'][i]\n",
      "C:\\Users\\LWJ\\AppData\\Local\\Temp\\ipykernel_22748\\888090635.py:34: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  height = data['Close'][i] - data['Open'][i]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# 假设的股票数据\n",
    "dates = pd.date_range('2025-01-01', periods=66)  # 生成100天的日期范围\n",
    "np.random.seed(0)  # 设置随机种子以便结果可重复\n",
    "open_prices = np.random.uniform(66, 166, size=len(dates))  # 随机生成开盘价\n",
    "high_prices = open_prices + np.random.uniform(0, 66, size=len(dates))  # 随机生成最高价\n",
    "low_prices = open_prices - np.random.uniform(0, 16, size=len(dates))  # 随机生成最低价\n",
    "close_prices = open_prices + np.random.uniform(-16, 16, size=len(dates))  # 随机生成收盘价\n",
    "\n",
    "# 将数据放入DataFrame中\n",
    "data = pd.DataFrame({\n",
    "    'Date': dates,\n",
    "    'Open': open_prices,\n",
    "    'High': high_prices,\n",
    "    'Low': low_prices,\n",
    "    'Close': close_prices\n",
    "})\n",
    "\n",
    "# 设置日期为索引\n",
    "data.set_index('Date', inplace=True)\n",
    "\n",
    "# 绘制股票图\n",
    "fig, ax = plt.subplots(figsize=(16, 6))\n",
    "\n",
    "# 绘制蜡烛图（K线图）\n",
    "for i in range(len(data)):\n",
    "    # 绘制上涨（绿色）和下跌（红色）的蜡烛\n",
    "    if data['Close'][i] >= data['Open'][i]:\n",
    "        color = 'g'  # 绿色表示上涨\n",
    "        lower = data['Open'][i]\n",
    "        height = data['Close'][i] - data['Open'][i]\n",
    "    else:\n",
    "        color = 'r'  # 红色表示下跌\n",
    "        lower = data['Close'][i]\n",
    "        height = data['Open'][i] - data['Close'][i]\n",
    "\n",
    "    # 绘制矩形（蜡烛的主体）\n",
    "    rect = plt.Rectangle((i-0.6, lower), 0.8, height, color=color)\n",
    "    ax.add_patch(rect)\n",
    "\n",
    "    # 绘制最高价和最低价的线\n",
    "    ax.plot([i-0.6, i+0.6], [data['High'][i], data['High'][i]], color='k')\n",
    "    ax.plot([i-0.6, i+0.6], [data['Low'][i], data['Low'][i]], color='k')\n",
    "\n",
    "# 设置x轴标签\n",
    "ax.set_xticks(range(len(data)))\n",
    "ax.set_xticklabels(data.index.strftime('%Y-%m-%d'), rotation=45)\n",
    "\n",
    "# 设置图例和标题\n",
    "ax.set_ylabel('Price')\n",
    "ax.set_title('Stock Price Chart')\n",
    "\n",
    "# 显示图表\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pymysql\n",
    "from sqlalchemy import create_engine\n",
    "engine = create_engine('mysql+pymysql://ropt:ps12345678@localhost/stock_basic')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting pyecharts\n",
      "  Downloading pyecharts-2.0.8-py3-none-any.whl.metadata (1.6 kB)\n",
      "Requirement already satisfied: jinja2 in d:\\anaconda\\lib\\site-packages (from pyecharts) (3.1.4)\n",
      "Collecting prettytable (from pyecharts)\n",
      "  Downloading prettytable-3.13.0-py3-none-any.whl.metadata (30 kB)\n",
      "Requirement already satisfied: simplejson in d:\\anaconda\\lib\\site-packages (from pyecharts) (3.19.3)\n",
      "Requirement already satisfied: MarkupSafe>=2.0 in d:\\anaconda\\lib\\site-packages (from jinja2->pyecharts) (2.1.3)\n",
      "Requirement already satisfied: wcwidth in d:\\anaconda\\lib\\site-packages (from prettytable->pyecharts) (0.2.5)\n",
      "Downloading pyecharts-2.0.8-py3-none-any.whl (153 kB)\n",
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      "   --------------------------------------- 153.7/153.7 kB 33.3 kB/s eta 0:00:00\n",
      "Downloading prettytable-3.13.0-py3-none-any.whl (31 kB)\n",
      "Installing collected packages: prettytable, pyecharts\n",
      "Successfully installed prettytable-3.13.0 pyecharts-2.0.8\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install pyecharts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x575 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import mplfinance as mpf\n",
    "\n",
    "# 手动创建数据帧（这里应该使用多日数据，但为了示例仍使用单日数据）\n",
    "data = {\n",
    "    'ts_code': ['920128.BJ', '920118.BJ'],  # 只选择前两个股票代码作为示例\n",
    "    'trade_date': ['20250126', '20250126'],\n",
    "    'open': [28.35, 24.10],\n",
    "    'high': [28.35, 24.59],\n",
    "    'low': [27.70, 24.01],\n",
    "    'close': [27.80, 24.42],\n",
    "    'pre_close': [27.94, 24.29],\n",
    "    'change': [-0.14, 0.13],\n",
    "    'pct_chg': [-0.5011, 0.5352],\n",
    "    'vol': [6781.63, 1835.70],  # 交易量数据列名为 'vol'\n",
    "    'amount': [18964.081, 4476.014]\n",
    "}\n",
    "\n",
    "# 将数据转换为DataFrame，并设置trade_date为索引\n",
    "df = pd.DataFrame(data)\n",
    "df['trade_date'] = pd.to_datetime(df['trade_date'])\n",
    "df.set_index('trade_date', inplace=True)\n",
    "\n",
    "# 选择其中一个股票的数据\n",
    "single_stock_df = df[df['ts_code'] == '920128.BJ'].drop(columns=['ts_code'])\n",
    "\n",
    "# 绘制K线图（不绘制交易量图）\n",
    "mpf.plot(single_stock_df, type='candle', style='charles', title='Stock Price Candlestick Chart for 920128.BJ', ylabel='Price')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sqlalchemy import create_engine\n",
    "\n",
    "# 假设您的数据是这样的字典列表（这里应该是一个列表，每个元素是一个字典，代表一行数据）\n",
    "data_list = [\n",
    "    {'ts_code': '920128.BJ', 'trade_date': '20250126', 'open': 28.35, 'high': 28.35, 'low': 27.70, 'close': 27.80, 'pre_close': 27.94, 'change': -0.14, 'pct_chg': -0.5011, 'vol': 6781.63, 'amount': 18964.081},\n",
    "    # ... 更多字典数据\n",
    "]\n",
    "\n",
    "# 将字典列表转换为 DataFrame\n",
    "df = pd.DataFrame(data_list)\n",
    "\n",
    "# 如果 trade_date 应该是日期时间类型，则转换它\n",
    "df['trade_date'] = pd.to_datetime(df['trade_date'])\n",
    "\n",
    "# Create SQLAlchemy engine\n",
    "engine = create_engine('mysql+pymysql://root:ps12345678@localhost/stock_data')\n",
    "\n",
    "# Use the engine to write the DataFrame to the database\n",
    "df.to_sql('stock_basic', con=engine, if_exists='replace', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5395 entries, 0 to 5394\n",
      "Data columns (total 10 columns):\n",
      " #   Column        Non-Null Count  Dtype \n",
      "---  ------        --------------  ----- \n",
      " 0   ts_code       5395 non-null   object\n",
      " 1   symbol        5395 non-null   object\n",
      " 2   name          5395 non-null   object\n",
      " 3   area          5380 non-null   object\n",
      " 4   industry      5380 non-null   object\n",
      " 5   cnspell       5395 non-null   object\n",
      " 6   market        5395 non-null   object\n",
      " 7   list_date     5395 non-null   object\n",
      " 8   act_name      2575 non-null   object\n",
      " 9   act_ent_type  2575 non-null   object\n",
      "dtypes: object(10)\n",
      "memory usage: 421.6+ KB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<bound method DataFrame.count of         ts_code  symbol     name  area industry cnspell market list_date  \\\n",
       "0     000001.SZ  000001     平安银行    深圳       银行    payh     主板  19910403   \n",
       "1     000002.SZ  000002      万科A    深圳     全国地产     wka     主板  19910129   \n",
       "2     000004.SZ  000004     国华网安    深圳     软件服务    ghwa     主板  19910114   \n",
       "3     000006.SZ  000006     深振业A    深圳     区域地产    szya     主板  19920427   \n",
       "4     000007.SZ  000007      全新好    深圳     其他商业     qxh     主板  19920413   \n",
       "...         ...     ...      ...   ...      ...     ...    ...       ...   \n",
       "5390  920111.BJ  920111     聚星科技  None     None    jxkj    北交所  20241111   \n",
       "5391  920116.BJ  920116     星图测控  None     None    xtck    北交所  20250102   \n",
       "5392  920118.BJ  920118     太湖远大  None     None    thyd    北交所  20240822   \n",
       "5393  920128.BJ  920128     胜业电气  None     None    sydq    北交所  20241129   \n",
       "5394  689009.SH  689009  九号公司-WD    北京      摩托车    jhgs    科创板  20201029   \n",
       "\n",
       "                act_name act_ent_type  \n",
       "0                 无实际控制人            无  \n",
       "1     深圳市人民政府国有资产监督管理委员会         地方国企  \n",
       "2                    李映彤         民营企业  \n",
       "3     深圳市人民政府国有资产监督管理委员会         地方国企  \n",
       "4                    王玩虹         民营企业  \n",
       "...                  ...          ...  \n",
       "5390                None         None  \n",
       "5391                None         None  \n",
       "5392                None         None  \n",
       "5393                None         None  \n",
       "5394                None         None  \n",
       "\n",
       "[5395 rows x 10 columns]>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tushare as ts\n",
    "pro = ts.pro_api('f78a738f8ce5bae4e6ebc54275bd2f404fc57e63500faa27db486cf1')\n",
    "data=pro.query('stock_basic',exchange='',list_status='L')\n",
    "data.info()\n",
    "data.count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20215 (\\N{CJK UNIFIED IDEOGRAPH-4EF7}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26684 (\\N{CJK UNIFIED IDEOGRAPH-683C}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 22797 (\\N{CJK UNIFIED IDEOGRAPH-590D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26434 (\\N{CJK UNIFIED IDEOGRAPH-6742}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 30340 (\\N{CJK UNIFIED IDEOGRAPH-7684}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 37329 (\\N{CJK UNIFIED IDEOGRAPH-91D1}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 34701 (\\N{CJK UNIFIED IDEOGRAPH-878D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20998 (\\N{CJK UNIFIED IDEOGRAPH-5206}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26512 (\\N{CJK UNIFIED IDEOGRAPH-6790}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 22270 (\\N{CJK UNIFIED IDEOGRAPH-56FE}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 34920 (\\N{CJK UNIFIED IDEOGRAPH-8868}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x575 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import mplfinance as mpf\n",
    "\n",
    "# 创建一个假设的K线图数据帧\n",
    "np.random.seed(0)\n",
    "dates = pd.date_range(start='2025-01-01', periods=100, freq='B')\n",
    "data = {\n",
    "    'Open': np.random.uniform(100, 200, size=len(dates)),\n",
    "    'High': np.random.uniform(105, 205, size=len(dates)),\n",
    "    'Low': np.random.uniform(95, 195, size=len(dates)),\n",
    "    'Close': np.random.uniform(100, 200, size=len(dates)),\n",
    "    'Volume': np.random.uniform(5000, 10000, size=len(dates)).astype(int)\n",
    "}\n",
    "df = pd.DataFrame(data, index=dates)\n",
    "\n",
    "# 计算移动平均线（MA）\n",
    "df['MA_50'] = df['Close'].rolling(window=50).mean()\n",
    "df['MA_200'] = df['Close'].rolling(window=200).mean()\n",
    "\n",
    "# 计算相对强弱指数（RSI），这里是一个简化的版本\n",
    "delta = df['Close'].diff()\n",
    "gain = (delta.where(delta > 0, 0)).rolling(window=14).mean()\n",
    "loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean()\n",
    "rs = gain / loss.replace(0, np.nan)  # 避免除以零\n",
    "rs = rs.fillna(1)  # 用1填充NaN值，以避免计算错误\n",
    "df['RSI'] = 100 - (100 / (1 + rs))\n",
    "# 创建自定义的mpf_style对象来定义图表的样式\n",
    "mpf_style = mpf.make_mpf_style(base_mpf_style='charles', rc={'font.size': 8})\n",
    "\n",
    "# 绘制复杂的金融分析图表\n",
    "apds = [\n",
    "    mpf.make_addplot(df['MA_50'], color='blue', secondary_y=False),\n",
    "    mpf.make_addplot(df['MA_200'], color='red', secondary_y=False),\n",
    "    mpf.make_addplot(df['RSI'], type='line', panel=1, color='green', secondary_y=True, ylabel='RSI')\n",
    "]\n",
    "\n",
    "mpf_kwargs = {\n",
    "    'type': 'candle',\n",
    "    'style': mpf_style,\n",
    "    'title': '复杂的金融分析图表',\n",
    "    'ylabel': '价格',\n",
    "    'volume': True,\n",
    "    'addplot': apds,\n",
    "    'panel_ratios': (6, 2),  # 调整主图和副图的比例\n",
    "    'figratio': (3, 2),      # 调整整个图表的长宽比（这将在内部被处理，不需要直接传递给mpf.plot）\n",
    "    'show_nontrading': False # 不显示非交易日\n",
    "}\n",
    "\n",
    "# 由于mpf.plot不支持直接返回图表对象，我们直接使用它来显示图表\n",
    "mpf.plot(df, **{k: v for k, v in mpf_kwargs.items() if k not in ['figratio']})  # 移除figratio，因为它不是有效参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: plotly in d:\\anaconda\\lib\\site-packages (5.22.0)\n",
      "Requirement already satisfied: tenacity>=6.2.0 in d:\\anaconda\\lib\\site-packages (from plotly) (8.2.2)\n",
      "Requirement already satisfied: packaging in d:\\anaconda\\lib\\site-packages (from plotly) (23.2)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install plotly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR: Could not find a version that satisfies the requirement force-reinstall (from versions: none)\n",
      "ERROR: No matching distribution found for force-reinstall\n"
     ]
    }
   ],
   "source": [
    "%pip install force-reinstall plotly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "Installing collected packages: nbformat\n",
      "  Attempting uninstall: nbformat\n",
      "    Found existing installation: nbformat 5.9.2\n",
      "    Uninstalling nbformat-5.9.2:\n",
      "      Successfully uninstalled nbformat-5.9.2\n",
      "Successfully installed nbformat-5.10.4\n",
      "Requirement already satisfied: nbformat in d:\\anaconda\\lib\\site-packages (5.9.2)\n",
      "Collecting nbformat\n",
      "  Using cached nbformat-5.10.4-py3-none-any.whl.metadata (3.6 kB)\n",
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      "Using cached nbformat-5.10.4-py3-none-any.whl (78 kB)\n",
      "Installing collected packages: nbformat\n",
      "  Attempting uninstall: nbformat\n",
      "    Found existing installation: nbformat 5.10.4\n",
      "    Uninstalling nbformat-5.10.4:\n",
      "      Successfully uninstalled nbformat-5.10.4\n",
      "Successfully installed nbformat-5.10.4\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: Skipping d:\\Anaconda\\Lib\\site-packages\\nbformat-5.9.2.dist-info due to invalid metadata entry 'name'\n"
     ]
    }
   ],
   "source": [
    "%pip install --upgrade nbformat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x575 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import mplfinance as mpf\n",
    "\n",
    "# 手动创建数据帧\n",
    "data = {\n",
    "    'ts_code': ['000001.SZ'] * 8,\n",
    "    'trade_date': [ '20180716', '20180713', '20180712','20180711', '20180710', '20180709', '20180706', '20180705'],\n",
    "    'open': [8.85, 8.92, 8.60, 8.76, 9.02, 8.69, 8.61, 8.62],\n",
    "    'high': [8.90, 8.94, 8.97, 8.83, 9.02, 9.03, 8.78, 8.73],\n",
    "    'low': [8.69, 8.82, 8.58, 8.68, 8.89, 8.68, 8.45, 8.55],\n",
    "    'close': [8.73, 8.88, 8.88, 8.78, 8.98, 9.03, 8.66, 8.60],\n",
    "    'pre_close': [8.88, 8.88, 8.64, 8.98, 9.03, 8.66, 8.60, 8.61],\n",
    "    'change': [-0.15, 0.00, 0.24, -0.20, -0.05, 0.37, 0.06, -0.01],\n",
    "    'pct_chg': [ -1.69, 0.00, 2.78, -2.23, -0.55, 4.27, 0.70, -0.12],\n",
    "    'vol': [ 689845.58, 603378.21, 1140492.31, 851296.70, 896862.02, 1409954.60, 988282.69, 835768.77],\n",
    "    'amount': [ 603427.713, 535401.175, 1008658.828, 744765.824, 803038.965, 1255007.609, 852071.526, 722169.579]\n",
    "}\n",
    "\n",
    "df = pd.DataFrame(data)\n",
    "\n",
    "# 将 trade_date 列转换为日期时间类型\n",
    "df['trade_date'] = pd.to_datetime(df['trade_date'], format='%Y%m%d')\n",
    "\n",
    "# 将 trade_date 列设置为索引\n",
    "df.set_index('trade_date', inplace=True)\n",
    "\n",
    "# 重命名 \"vol\" 列为 \"volume\"\n",
    "df.rename(columns={'vol': 'volume'}, inplace=True)\n",
    "\n",
    "# 绘制 K 线图\n",
    "mpf.plot(df, type='candle', style='yahoo', title='000001.SZ K-line Chart',\n",
    "         ylabel='Price', volume=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting plotly\n",
      "  Using cached plotly-5.24.1-py3-none-any.whl.metadata (7.3 kB)\n",
      "Collecting tenacity>=6.2.0 (from plotly)\n",
      "  Using cached tenacity-9.0.0-py3-none-any.whl.metadata (1.2 kB)\n",
      "Collecting packaging (from plotly)\n",
      "  Using cached packaging-24.2-py3-none-any.whl.metadata (3.2 kB)\n",
      "Using cached plotly-5.24.1-py3-none-any.whl (19.1 MB)\n",
      "Using cached tenacity-9.0.0-py3-none-any.whl (28 kB)\n",
      "Using cached packaging-24.2-py3-none-any.whl (65 kB)\n",
      "Installing collected packages: tenacity, packaging, plotly\n",
      "  Attempting uninstall: tenacity\n",
      "    Found existing installation: tenacity 9.0.0\n",
      "    Uninstalling tenacity-9.0.0:\n",
      "      Successfully uninstalled tenacity-9.0.0\n",
      "  Attempting uninstall: packaging\n",
      "    Found existing installation: packaging 24.2\n",
      "    Uninstalling packaging-24.2:\n",
      "      Successfully uninstalled packaging-24.2\n",
      "  Attempting uninstall: plotly\n",
      "    Found existing installation: plotly 5.24.1\n",
      "    Uninstalling plotly-5.24.1:\n",
      "      Successfully uninstalled plotly-5.24.1\n",
      "Successfully installed packaging-24.2 plotly-5.24.1 tenacity-9.0.0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "streamlit 1.32.0 requires packaging<24,>=16.8, but you have packaging 24.2 which is incompatible.\n",
      "streamlit 1.32.0 requires tenacity<9,>=8.1.0, but you have tenacity 9.0.0 which is incompatible.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting djangoNote: you may need to restart the kernel to use updated packages.\n",
      "\n",
      "  Using cached Django-5.1.5-py3-none-any.whl.metadata (4.2 kB)\n",
      "Collecting asgiref<4,>=3.8.1 (from django)\n",
      "  Using cached asgiref-3.8.1-py3-none-any.whl.metadata (9.3 kB)\n",
      "Collecting sqlparse>=0.3.1 (from django)\n",
      "  Using cached sqlparse-0.5.3-py3-none-any.whl.metadata (3.9 kB)\n",
      "Requirement already satisfied: tzdata in d:\\anaconda\\lib\\site-packages (from django) (2023.3)\n",
      "Downloading Django-5.1.5-py3-none-any.whl (8.3 MB)\n",
      "   ---------------------------------------- 0.0/8.3 MB ? eta -:--:--\n",
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      "Downloading asgiref-3.8.1-py3-none-any.whl (23 kB)\n",
      "Downloading sqlparse-0.5.3-py3-none-any.whl (44 kB)\n",
      "   ---------------------------------------- 0.0/44.4 kB ? eta -:--:--\n",
      "   ---------------------------------------- 44.4/44.4 kB 2.3 MB/s eta 0:00:00\n",
      "Installing collected packages: sqlparse, asgiref, django\n",
      "Successfully installed asgiref-3.8.1 django-5.1.5 sqlparse-0.5.3\n"
     ]
    }
   ],
   "source": [
    "%pip install django"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20215 (\\N{CJK UNIFIED IDEOGRAPH-4EF7}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26684 (\\N{CJK UNIFIED IDEOGRAPH-683C}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 32929 (\\N{CJK UNIFIED IDEOGRAPH-80A1}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 31080 (\\N{CJK UNIFIED IDEOGRAPH-7968}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 36208 (\\N{CJK UNIFIED IDEOGRAPH-8D70}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21183 (\\N{CJK UNIFIED IDEOGRAPH-52BF}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 22270 (\\N{CJK UNIFIED IDEOGRAPH-56FE}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20132 (\\N{CJK UNIFIED IDEOGRAPH-4EA4}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26131 (\\N{CJK UNIFIED IDEOGRAPH-6613}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26085 (\\N{CJK UNIFIED IDEOGRAPH-65E5}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26399 (\\N{CJK UNIFIED IDEOGRAPH-671F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 25910 (\\N{CJK UNIFIED IDEOGRAPH-6536}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 30424 (\\N{CJK UNIFIED IDEOGRAPH-76D8}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 24320 (\\N{CJK UNIFIED IDEOGRAPH-5F00}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "# 假设你的数据已经保存在一个名为data的字典中，这里我们直接使用你提供的数据\n",
    "data = {\n",
    "    'ts_code': ['000001.SZ'] * 22,\n",
    "    'trade_date': pd.to_datetime(['20181031', '20180930', '20180831', '20180731', '20180630', '20180531', '20180430', '20180331', '20180228', '20180131', '20171231', '20171130', '20171031', '20170930', '20170831', '20170731', '20170630', '20170531', '20170430', '20170331', '20170228', '20170131']),\n",
    "    'close': [10.91, 11.05, 10.13, 9.42, 9.09, 10.18, 10.85, 10.90, 12.05, 14.05, 13.30, 13.38, 11.54, 11.11, 11.28, 10.67, 9.39, 9.20, 8.99, 9.17, 9.48, 9.33],\n",
    "    'open': [10.70, 10.09, 9.42, 9.05, 10.15, 10.97, 10.87, 11.92, 13.95, 13.35, 13.40, 11.56, 11.57, 11.28, 10.64, 9.40, 9.20, 8.96, 9.16, 9.49, 9.34, 9.11],\n",
    "    'high': [11.46, 11.27, 10.43, 9.59, 10.46, 11.23, 11.94, 12.34, 14.57, 15.13, 13.86, 15.24, 11.73, 11.94, 11.74, 11.33, 9.49, 9.23, 9.22, 9.55, 9.62, 9.34],\n",
    "    'low': [9.70, 9.68, 8.64, 8.45, 8.87, 10.02, 10.51, 10.55, 11.38, 12.86, 12.64, 11.09, 11.12, 10.82, 9.99, 9.27, 8.99, 8.54, 8.89, 9.06, 9.23, 9.07],\n",
    "    # 'vol' 和 'amount' 字段在此示例中未使用，但可以根据需要添加\n",
    "}\n",
    "\n",
    "# 创建DataFrame\n",
    "df = pd.DataFrame(data)\n",
    "\n",
    "# 设置绘图风格（可选）\n",
    "plt.style.use('ggplot')\n",
    "\n",
    "# 创建一个图形\n",
    "fig, ax = plt.subplots(figsize=(10, 5))\n",
    "\n",
    "# 绘制收盘价\n",
    "ax.plot(df['trade_date'], df['close'], label='收盘价', color='r')\n",
    "\n",
    "# 绘制开盘价\n",
    "ax.plot(df['trade_date'], df['open'], label='开盘价', color='g')\n",
    "\n",
    "# 绘制最高价和最低价之间的区域\n",
    "ax.fill_between(df['trade_date'], df['low'], df['high'], color='k', alpha=0.1)\n",
    "# 设置标题和标签\n",
    "ax.set_title('股票价格走势图')\n",
    "ax.set_xlabel('交易日期')\n",
    "ax.set_ylabel('价格')\n",
    "\n",
    "# 显示图例\n",
    "ax.legend()\n",
    "\n",
    "# 设置x轴日期格式\n",
    "ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
    "ax.xaxis.set_major_locator(mdates.DayLocator())\n",
    "\n",
    "# 自动调整子图参数, 使之填充整个图像区域（对于日期标签特别有用）\n",
    "fig.autofmt_xdate()\n",
    "\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:33: SyntaxWarning: invalid escape sequence '\\s'\n",
      "<>:33: SyntaxWarning: invalid escape sequence '\\s'\n",
      "C:\\Users\\LWJ\\AppData\\Local\\Temp\\ipykernel_20880\\115630571.py:33: SyntaxWarning: invalid escape sequence '\\s'\n",
      "  df = pd.read_csv(StringIO(data), sep='\\s+')\n",
      "C:\\Users\\LWJ\\AppData\\Local\\Temp\\ipykernel_20880\\115630571.py:46: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  ohlc.rename(columns={'vol': 'volume'}, inplace=True)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x575 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import mplfinance as mpf\n",
    "\n",
    "# 定义数据\n",
    "data = \"\"\"\n",
    "ts_code trade_date  close   open   high    low          vol  amount\n",
    "000001.SZ   20181031  10.91  10.70  11.46   9.70  27801557.09  2.960878e+07\n",
    "000001.SZ   20180930  11.05  10.09  11.27   9.68  18821004.99  1.942842e+07\n",
    "000001.SZ   20180831  10.13   9.42  10.43   8.64  21896873.02  2.088672e+07\n",
    "000001.SZ   20180731   9.42   9.05   9.59   8.45  20430278.02  1.832737e+07\n",
    "000001.SZ   20180630   9.09  10.15  10.46   8.87  18179888.58  1.791251e+07\n",
    "000001.SZ   20180531  10.18  10.97  11.23  10.02  18267177.83  1.965278e+07\n",
    "000001.SZ   20180430  10.85  10.87  11.94  10.51  23495990.53  2.655691e+07\n",
    "000001.SZ   20180331  10.90  11.92  12.34  10.55  23129969.15  2.692560e+07\n",
    "000001.SZ   20180228  12.05  13.95  14.57  11.38  25624473.21  3.322504e+07\n",
    "000001.SZ   20180131  14.05  13.35  15.13  12.86  46145376.46  6.454870e+07\n",
    "000001.SZ   20171231  13.30  13.40  13.86  12.64  29661838.16  3.914290e+07\n",
    "000001.SZ   20171130  13.38  11.56  15.24  11.09  42481293.87  5.604279e+07\n",
    "000001.SZ   20171031  11.54  11.57  11.73  11.12  13951964.07  1.597217e+07\n",
    "000001.SZ   20170930  11.11  11.28  11.94  10.82  16101838.41  1.827867e+07\n",
    "00001.SZ   20170831  11.28  10.64  11.74   9.99  26281362.76  2.859479e+07\n",
    "000001.SZ   20170731  10.67   9.40  11.33   9.27  35360949.04  3.736988e+07\n",
    "000001.SZ   20170630   9.39   9.20   9.49   8.99  12718091.74  1.171552e+07\n",
    "000001.SZ   20170531   9.20   8.96   9.23   8.54  12252646.46  1.083921e+07\n",
    "000001.SZ   20170430   8.99   9.16   9.22   8.89   8024338.26  7.268941e+06\n",
    "000001.SZ   20170331   9.17   9.49   9.55   9.06  12889345.37  1.197751e+07\n",
    "000001.SZ   20170228   9.48   9.34   9.62   9.23   8460527.09  7.977982e+06\n",
    "000001.SZ   20170131   9.33   9.11   9.34   9.07   7629258.66  7.001209e+06\n",
    "\"\"\"\n",
    "# 将数据加载到 DataFrame 中\n",
    "from io import StringIO\n",
    "df = pd.read_csv(StringIO(data), sep='\\s+')\n",
    "\n",
    "# 将 trade_date 列转换为日期类型\n",
    "df['trade_date'] = pd.to_datetime(df['trade_date'], format='%Y%m%d')\n",
    "\n",
    "# 将 trade_date 列设置为索引\n",
    "df.set_index('trade_date', inplace=True)\n",
    "\n",
    "# 对数据进行排序\n",
    "df = df.sort_index()\n",
    "\n",
    "# 选择需要的列\n",
    "ohlc = df[['open', 'high', 'low', 'close', 'vol']]\n",
    "ohlc.rename(columns={'vol': 'volume'}, inplace=True)\n",
    "\n",
    "# 绘制 K 线图\n",
    "mpf.plot(ohlc, type='candle', volume=True, title='Stock Candlestick Chart', ylabel='Price', ylabel_lower='Volume')\n",
    "\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:32: SyntaxWarning: invalid escape sequence '\\s'\n",
      "<>:32: SyntaxWarning: invalid escape sequence '\\s'\n",
      "C:\\Users\\LWJ\\AppData\\Local\\Temp\\ipykernel_2952\\1162500606.py:32: SyntaxWarning: invalid escape sequence '\\s'\n",
      "  df = pd.read_csv(StringIO(data), sep='\\s+')\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1920x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 定义数据\n",
    "data = \"\"\"\n",
    "trade_date    ts_code  up_limit  down_limit\n",
    "20190625  000001.SZ     15.06       12.32\n",
    "20190625  000002.SZ     30.94       25.32\n",
    "20190625  000004.SZ     25.15       20.57\n",
    "20190625  000005.SZ      3.49        2.85\n",
    "20190625  000006.SZ      6.14        5.02\n",
    "20190625  000007.SZ      7.74        6.34\n",
    "20190625  000008.SZ      4.28        3.50\n",
    "20190625  000009.SZ      6.36        5.20\n",
    "20190625  000010.SZ      3.51        3.17\n",
    "20190625  000011.SZ     10.58        8.66\n",
    "20190625  000012.SZ      5.16        4.22\n",
    "20190625  000014.SZ     10.98        8.98\n",
    "20190625  000016.SZ      4.81        3.93\n",
    "20190625  000017.SZ      5.15        4.21\n",
    "20190625  000018.SZ      1.44        1.30\n",
    "20190625  000019.SZ      8.09        6.62\n",
    "20190625  000020.SZ     12.21        9.99\n",
    "20190625  000021.SZ      9.30        7.61\n",
    "20190625  000023.SZ     14.61       11.95\n",
    "20190625  000025.SZ     23.08       18.88\n",
    "20190625  000026.SZ      8.66        7.08\n",
    "\"\"\"\n",
    "\n",
    "# 从字符串读取数据到 DataFrame\n",
    "from io import StringIO\n",
    "df = pd.read_csv(StringIO(data), sep='\\s+')\n",
    "\n",
    "# 设置图片清晰度\n",
    "plt.rcParams['figure.dpi'] = 300\n",
    "\n",
    "# 设置中文字体\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "# 解决负号显示问题\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "# 绘制涨跌停价格柱状图\n",
    "x = range(len(df['ts_code']))\n",
    "width = 0.35\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "rects1 = ax.bar([i - width/2 for i in x], df['up_limit'], width, label='涨停价')\n",
    "rects2 = ax.bar([i + width/2 for i in x], df['down_limit'], width, label='跌停价')\n",
    "\n",
    "# 添加数据标签\n",
    "def autolabel(rects):\n",
    "    for rect in rects:\n",
    "        height = rect.get_height()\n",
    "        ax.annotate('{:.2f}'.format(height),\n",
    "                    xy=(rect.get_x() + rect.get_width() / 2, height),\n",
    "                    xytext=(0, 3),  # 3 points vertical offset\n",
    "                    textcoords=\"offset points\",\n",
    "                    ha='center', va='bottom')\n",
    "\n",
    "autolabel(rects1)\n",
    "autolabel(rects2)\n",
    "\n",
    "# 设置图形标题和坐标轴标签\n",
    "ax.set_ylabel('价格')\n",
    "ax.set_title('2019年6月25日部分股票涨跌停价格')\n",
    "ax.set_xticks(x)\n",
    "ax.set_xticklabels(df['ts_code'], rotation=90)\n",
    "ax.legend()\n",
    "\n",
    "# 显示图形\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import mysql.connector\n",
    "import matplotlib.pyplot as plt\n",
    "import mplfinance as mpf  # 用于绘制金融图表的库，是matplotlib的扩展\n",
    "\n",
    "# MySQL数据库连接配置\n",
    "config = {\n",
    "    'user': 'root',\n",
    "    'password': 'wxyKF2004',\n",
    "    'host': 'localhost',\n",
    "    'database': 'stock_data',\n",
    "    'raise_on_warnings': True\n",
    "}\n",
    "\n",
    "# 连接到MySQL数据库\n",
    "cnx = mysql.connector.connect(**config)\n",
    "\n",
    "# 查询stock_data表中的数据\n",
    "query = \"SELECT trade_date, open, high, low, close FROM stock_data ORDER BY trade_date\"\n",
    "df = pd.read_sql(query, cnx)\n",
    "\n",
    "# 将trade_date列转换为datetime类型，并设置为索引\n",
    "df['trade_date'] = pd.to_datetime(df['trade_date'], format='%Y%m%d')\n",
    "df.set_index('trade_date', inplace=True)\n",
    "\n",
    "# 关闭数据库连接\n",
    "cnx.close()\n",
    "\n",
    "# 使用mplfinance绘制K线图\n",
    "df.rename(columns={'open': 'Open', 'high': 'High', 'low': 'Low', 'close': 'Close'}, inplace=True)  # 重命名列以匹配mplfinance的期望\n",
    "mpf.plot(df, type='candle', style='charles', title='Stock Price K-Line Chart', ylabel='Price')\n",
    "\n",
    "# 显示图表\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 19978 (\\N{CJK UNIFIED IDEOGRAPH-4E0A}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 28023 (\\N{CJK UNIFIED IDEOGRAPH-6D77}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26426 (\\N{CJK UNIFIED IDEOGRAPH-673A}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 22330 (\\N{CJK UNIFIED IDEOGRAPH-573A}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 23453 (\\N{CJK UNIFIED IDEOGRAPH-5B9D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 38050 (\\N{CJK UNIFIED IDEOGRAPH-94A2}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 32929 (\\N{CJK UNIFIED IDEOGRAPH-80A1}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20221 (\\N{CJK UNIFIED IDEOGRAPH-4EFD}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 25307 (\\N{CJK UNIFIED IDEOGRAPH-62DB}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21830 (\\N{CJK UNIFIED IDEOGRAPH-5546}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 38134 (\\N{CJK UNIFIED IDEOGRAPH-94F6}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 34892 (\\N{CJK UNIFIED IDEOGRAPH-884C}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 24658 (\\N{CJK UNIFIED IDEOGRAPH-6052}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 29790 (\\N{CJK UNIFIED IDEOGRAPH-745E}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21307 (\\N{CJK UNIFIED IDEOGRAPH-533B}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 33647 (\\N{CJK UNIFIED IDEOGRAPH-836F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 36149 (\\N{CJK UNIFIED IDEOGRAPH-8D35}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 24030 (\\N{CJK UNIFIED IDEOGRAPH-5DDE}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 33541 (\\N{CJK UNIFIED IDEOGRAPH-8305}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21488 (\\N{CJK UNIFIED IDEOGRAPH-53F0}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 34746 (\\N{CJK UNIFIED IDEOGRAPH-87BA}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 27700 (\\N{CJK UNIFIED IDEOGRAPH-6C34}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 27877 (\\N{CJK UNIFIED IDEOGRAPH-6CE5}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 38738 (\\N{CJK UNIFIED IDEOGRAPH-9752}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 23707 (\\N{CJK UNIFIED IDEOGRAPH-5C9B}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 23572 (\\N{CJK UNIFIED IDEOGRAPH-5C14}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20234 (\\N{CJK UNIFIED IDEOGRAPH-4F0A}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21033 (\\N{CJK UNIFIED IDEOGRAPH-5229}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20013 (\\N{CJK UNIFIED IDEOGRAPH-4E2D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 22269 (\\N{CJK UNIFIED IDEOGRAPH-56FD}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 24179 (\\N{CJK UNIFIED IDEOGRAPH-5E73}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 23433 (\\N{CJK UNIFIED IDEOGRAPH-5B89}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 25910 (\\N{CJK UNIFIED IDEOGRAPH-6536}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 30424 (\\N{CJK UNIFIED IDEOGRAPH-76D8}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20215 (\\N{CJK UNIFIED IDEOGRAPH-4EF7}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "d:\\Anaconda\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26053 (\\N{CJK UNIFIED IDEOGRAPH-65C5}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 800x2000 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import io\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "import matplotlib as mpl\n",
    "\n",
    "# 设置全局字体大小（可选）\n",
    "mpl.rcParams['font.size'] = 8\n",
    "\n",
    "# 你的数据字符串（这里为了示例简化，实际使用时你应该有完整的数据字符串）\n",
    "data = \"\"\"\n",
    "trade_date,ts_code,name,close,change,rank,market_type,amount,net_amount,buy,sell\n",
    "20180725,600009.SH,上海机场,62.69,2.0677,9,1,240958518.0,31199144.0,136078831.0,104879687.0\n",
    "20180725,600019.SH,宝钢股份,8.62,0.9368,7,1,245582396.0,81732606.0,163657501.0,81924895.0\n",
    "20180725,600036.SH,招商银行,28.22,1.6937,10,1,240655550.0,142328622.0,191492086.0,49163464.0\n",
    "20180725,600276.SH,恒瑞医药,71.89,1.2393,5,1,329472455.0,-71519443.0,128976506.0,200495949.0\n",
    "20180725,600519.SH,贵州茅台,743.81,-0.2133,2,1,508590993.0,226149667.0,367370330.0,141220663.0\n",
    "20180725,600585.SH,海螺水泥,38.23,-0.4427,3,1,357946144.0,51215890.0,204581017.0,153365127.0\n",
    "20180725,600690.SH,青岛海尔,18.09,0.0000,8,1,243840019.0,-55595149.0,94122435.0,149717584.0\n",
    "20180725,600887.SH,伊利股份,27.54,-1.7131,6,1,296552611.0,-40273759.0,128139426.0,168413185.0\n",
    "20180725,601318.SH,中国平安,62.16,0.6803,1,1,534002916.0,287838388.0,410920652.0,123082264.0\n",
    "20180725,601888.SH,中国国旅,74.19,5.5184,4,1,342115066.0,-63262966.0,139426050.0,202689016.0\n",
    "\"\"\"\n",
    "\n",
    "# 使用 io.StringIO 来加载数据\n",
    "data_stream = io.StringIO(data)\n",
    "df = pd.read_csv(data_stream)\n",
    "\n",
    "# 将 trade_date 列转换为日期格式\n",
    "df['trade_date'] = pd.to_datetime(df['trade_date'], format='%Y%m%d')\n",
    "\n",
    "# 设置绘图风格（可选）\n",
    "plt.style.use('ggplot')\n",
    "\n",
    "# 创建一个图形和多个子图，调整 figsize 以适应更小的子图\n",
    "fig, axes = plt.subplots(nrows=len(df['ts_code'].unique()), figsize=(8, len(df['ts_code'].unique()) * 2), sharex=True)\n",
    "\n",
    "# 处理只有一个子图的情况\n",
    "if isinstance(axes, plt.Axes):\n",
    "    axes = [axes]\n",
    "\n",
    "# 绘制每个股票的收盘价\n",
    "for ax, (ts_code, group) in zip(axes, df.groupby('ts_code')):\n",
    "    ax.plot(group['trade_date'], group['close'], marker='o', label=group['name'].iloc[0] if ax == axes[0] else None)  # 只在第一个子图上显示图例\n",
    "    ax.set_title(group['name'].iloc[0], fontsize=9)  # 调整标题字体大小\n",
    "    ax.set_ylabel('收盘价', fontsize=9)  # 调整 y 轴标签字体大小\n",
    "    ax.grid(True, which='both', linestyle='--', linewidth=0.5)  # 自定义网格线样式\n",
    "    ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
    "    ax.xaxis.set_major_locator(mdates.DayLocator())\n",
    "    ax.tick_params(axis='both', which='major', labelsize=8)  # 调整刻度标签字体大小\n",
    "\n",
    "# 隐藏除了最后一个子图之外的所有子图的 x 轴刻度标签和 y 轴标签（除了第一个）\n",
    "for ax in axes[:-1]:\n",
    "    ax.set_xticklabels([])\n",
    "    ax.set_ylabel('')  # 隐藏 y 轴标签（除了第一个子图）\n",
    "\n",
    "# 只在最后一个子图上显示 x 轴标签\n",
    "axes[-1].xaxis.set_tick_params(labelbottom=True)\n",
    "\n",
    "# 调整子图之间的间距\n",
    "plt.subplots_adjust(hspace=0.3, wspace=0)\n",
    "\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
